Data Source: Yahoo

Looking at Stock Prices of Tesla VS. Other Automotive Companies:

Code

library(quantmod)
library(plotly)

options("getSymbols.warning4.0"=FALSE)
options("getSymbols.yahoo.warning"=FALSE)

tickers = c("STLA","GM", "TM","NSANY", "MBGYY", "BMWYY","POAHY", "TSLA" )

getSymbols(tickers,auto.assign = TRUE, src="yahoo")

for (i in tickers){
  getSymbols(i,
             from = "2018-01-01",
             to = Sys.Date())}

x <- list(
  title = "date"
)
y <- list(
  title = "value"
)

stock <- data.frame(STLA$STLA.Adjusted,
                    GM$GM.Adjusted,
                    TM$TM.Adjusted,
                    NSANY$NSANY.Adjusted,
                    MBGYY$MBGYY.Adjusted,
                    BMWYY$BMWYY.Adjusted,
                    POAHY$POAHY.Adjusted,
                    TSLA$TSLA.Adjusted)


stock <- data.frame(stock,rownames(stock))

colnames(stock) <- append(tickers,'Dates')
head(stock)

stock$Dates<-as.Date(stock$Dates,"%Y-%m-%d")
str(stock)

g <- ggplot(stock, aes(x=Dates)) +
  geom_line(aes(y=STLA, colour="STLA"))+ 
  geom_line(aes(y=GM, colour="GM"))+
  geom_line(aes(y=TM, colour="TM"))+ 
  geom_line(aes(y=NSANY, colour="NSANY"))+ 
  geom_line(aes(y=MBGYY, colour="MBGYY"))+
  geom_line(aes(y=BMWYY, colour="BMWYY"))+ 
  geom_line(aes(y=POAHY, colour="POAHY"))+ 
  geom_line(aes(y=TSLA, colour="TSLA"))+ 
  labs(
    title = "Stock Prices for Automotive Companies",
    subtitle = "From 2018-2023",
    x = "Date",
    y = "Adjusted Closing Prices")+
    guides(colour=guide_legend(title="Automotive Companies")) 

ggplotly(g) %>%
  layout(hovermode = "x")

# Save the dataframe to a CSV file
write.csv(stock, file = "stock.csv", row.names = FALSE)

Loading required package: xts

Loading required package: zoo


Attaching package: 'zoo'


The following objects are masked from 'package:base':

    as.Date, as.Date.numeric


Loading required package: TTR

Registered S3 method overwritten by 'quantmod':
  method            from
  as.zoo.data.frame zoo 

Loading required package: ggplot2


Attaching package: 'plotly'


The following object is masked from 'package:ggplot2':

    last_plot


The following object is masked from 'package:stats':

    filter


The following object is masked from 'package:graphics':

    layout

1. 'STLA'
2. 'GM'
3. 'TM'
4. 'NSANY'
5. 'MBGYY'
6. 'BMWYY'
7. 'POAHY'
8. 'TSLA'

A data.frame: 6 × 9

	STLA	GM	TM	NSANY	MBGYY	BMWYY	POAHY	TSLA	Dates
	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<chr>
2018-01-02	11.47271	37.49935	128.37	20.04	15.42706	25.13300	6.742719	21.36867	2018-01-02
2018-01-03	11.94581	38.41441	130.13	20.25	15.54485	25.27038	6.887549	21.15000	2018-01-03
2018-01-04	12.85466	39.59860	132.16	20.23	15.75144	25.44391	7.072612	20.97467	2018-01-04
2018-01-05	13.55187	39.48196	133.86	20.39	15.93447	25.74035	7.145028	21.10533	2018-01-05
2018-01-08	13.43359	39.67036	134.77	20.44	16.00333	25.91389	7.161120	22.42733	2018-01-08
2018-01-09	13.67637	39.51786	133.72	20.54	16.04138	25.99342	7.225490	22.24600	2018-01-09

'data.frame':   1490 obs. of  9 variables:
 $ STLA : num  11.5 11.9 12.9 13.6 13.4 ...
 $ GM   : num  37.5 38.4 39.6 39.5 39.7 ...
 $ TM   : num  128 130 132 134 135 ...
 $ NSANY: num  20 20.2 20.2 20.4 20.4 ...
 $ MBGYY: num  15.4 15.5 15.8 15.9 16 ...
 $ BMWYY: num  25.1 25.3 25.4 25.7 25.9 ...
 $ POAHY: num  6.74 6.89 7.07 7.15 7.16 ...
 $ TSLA : num  21.4 21.1 21 21.1 22.4 ...
 $ Dates: Date, format: "2018-01-02" "2018-01-03" ...

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Data from Bloomberg:

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